Blood pressure is a key metric of cardiovascular health, but standard methods for measuring it rely on occasional readings ...

Machine learning is becoming an essential part of a physicist’s toolkit. How should new students learn to use it? When Radha Mastandrea started her undergraduate physics program at MIT in 2015, she ...

Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries? Theoretical ...

See more of our trusted coverage when you search. Prefer Newsweek on Google to see more of our trusted coverage when you search. John Hopfield and Geoffrey Hinton were awarded the 2024 Nobel Prize in ...

For years, machine learning in physics meant automating tedious tasks, from sorting particle collisions to cleaning detector noise. That role is still vital, but the ambition has shifted toward using ...

The 2024 Nobel prize in physics has been awarded to John Hopfield and Geoffrey Hinton for their work on artificial neural networks and the fundamental algorithms that let machines learn, which are key ...

Two scientists have been awarded the Nobel Prize in Physics "for foundational discoveries and inventions that enable machine learning with artificial neural networks." John Hopfield, an emeritus ...

• A new AI machine learning algorithm capable of predicting planetary orbits that may one day help accelerate physics research in other areas such as renewable energy. • Strikingly, the algorithms ...

On April 21, 2026, the Faculty of Natural and Applied Sciences (FONAS) at Lead City University hosted its Annual Faculty Lecture at the International Conference Center, delivering a timely and ...